Prediction of response to kinase inhibitors based on protein phosphorylation profiles in tumor tissue from advanced renal cell cancer patients

Completed

Conditions: kidney cancer
Renal cell cancer
10038364

Registration Number: NL-OMON37502

Lead Sponsor: Vrije Universiteit Medisch Centrum

Brief Summary: Not available

Detailed Description: Not available

Recruitment & Eligibility

Status: Completed

Sex: Not specified

Target Recruitment: 225

Inclusion Criteria

• Patients with advanced (unresectable and/or metastatic) renal cell cancer;
• Patients who will start treatment with sunitinib, pazopanib, sorafenib, axitinib or everolimus;
• At least one tumor lesion should be accessible for biopsy. Bone metastases are excluded as possible biopsy site;
• Age >- 18 years;
• Patients must have at least one measurable lesion. Lesions must be evaluated by CT-scan or MRI according to Response Evaluation Criteria in Solid Tumors (RECIST);
• WHO performance status 0 - 2;
• Able to provide written informed consent;

Exclusion Criteria

• Clinical findings associated with an unacceptably high tumor biopsy risk, according to the judgement of the investigator;
• Radiotherapy on target lesions during study or within 4 weeks of the start of study drug;
• Any condition that is unstable or could jeopardize the safety of the subject and their compliance in the study;

Study & Design

Study Type: Observational invasive

Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
<p>Pretreatment tumor tissue phosphoproteomic profile, radiological response to<br /><br>standard treatment, PFS.<br /><br><br /><br>Phosphoproteomic profiles will be determined from the tumor biopsy and<br /><br>correlated to radiological response and PFS. Phosphotyrosine signaling pathways<br /><br>aberrantly activated in individual subgroups, identified by unsupervised<br /><br>hierarchical clustering, will be examined in relation to the clinical effect of<br /><br>the different kinase inhibitors. The classifier will be based on activity of<br /><br>one or multiple signaling pathways and protein networks and will be subjected<br /><br>to an internal validation such as the ten-fold cross validation technique to<br /><br>estimate its generalization performance.<br /><br><br /><br>Primary endpoint: Prediction accuracy of the phosphoproteomic classifier</p><br>

Secondary Outcome Measures

Name	Time	Method
<p>-To determine the relation between pre-treatment PamChip kinase activity<br /><br>profiling and PFS<br /><br>-To determine whether genome-wide mutational profiles by Massively Parallel<br /><br>Sequencing (MPS) can be related to PFS<br /><br>-To determine whether both pre- and on-treatment serum proteomic profiles are<br /><br>related to PFS<br /><br>-To determine the value of the frequency and phenotype of immunoregulatory<br /><br>cells in blood and tumor tissue for treatment response prediction.<br /><br>-To determine the relation between genetic polymorphisms and pharmacokinetic<br /><br>parameters (systemic and intratumoral drug concentrations) and PFS.<br /><br>-To determine the value of tumor exosomes from urine and serum as potential<br /><br>source of biomarkers.</p><br>